Automatic Video Summarization by Graph Modeling

Authors:
Chong-Wah Ngo;Yu-Fei Ma;Hong-Jiang Zhang
Affiliations:
-;-;-
Venue:
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Year:
2003

Citing 0
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Abstract

We propose a unified approach for summarization based on theanalysis of video structures and video highlights. Our approachemphasizes both the content balance and perceptual quality of asummary. Normalized cut algorithm is employed to globally andoptimally partition a video into clusters. A motion attention modelbased on human perception is employed to compute the perceptualquality of shots and clusters. The clusters, together with thecomputed attention values, form a temporal graph similar to Markovchain that inherently describes the evolution and perceptualimportance of video clusters. In our application, the flow of atemporal graph is utilized to group similar clusters into scenes,while the attention values are used as guidelines to selectappropriate sub-shots in scenes for summarization.